CROP YIELD PREDICTION BASED ON MACHINE LEARNING

In order to find relevant information and draw recommendations, the data analysis process involves analyzing, cleaning, modeling data. India has a large population, hence it is important protect world's food supply despite climate fluctuations.Framers face serious problems in drought conditions.The agricultural output significantly influenced by kind of soil. Advising farmers utilize fertilizers might assist them making best choice possible for their farming circumstances. There are several studies Information Communication Technology (ICT) may be used yield prediction. We can also anticipate production using mining. advise farmer plant better crop higher thoroughly analyzing prior from traditional transferred educated through smart agriculture. calculate estimates overall physical functions yields various crops given condition, taking into account newly designed weather index as an input.To adequately compare our actual result, known target, with prediction model, which provides rice based on available data, regression coefficient determination well average error rate were conducted. To increase production, mining approaches employed estimate output. For operational projects, crucial accurately promptly evaluate state predict yields. The goal this study employ variety forecasting techniques assess estimations Ghana due significance Crop prediction, offers decision-makers.